Mendelian Randomization Studies of Cancer Risk: a Literature Review
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Purpose of Review
In this paper, we summarize prior studies that have used Mendelian randomization (MR) methods to study the effects of exposures, lifestyle factors, physical traits, and/or biomarkers on cancer risk in humans. Many such risk factors have been associated with cancer risk in observational studies, and the MR approach can be used to provide evidence as to whether these associations represent causal relationships. MR methods require a risk factor of interest to have known genetic determinants that can be used as proxies for the risk factor (i.e., “instrumental variables” or IVs), and these can be used to obtain an effect estimate that, under certain assumptions, is not prone to bias caused by unobserved confounding or reverse causality. This review seeks to describe how MR studies have contributed to our understanding of cancer causation.
We searched the published literature and identified 76 MR studies of cancer risk published prior to October 31, 2017. Risk factors commonly studied included alcohol consumption, vitamin D, anthropometric traits, telomere length, lipid traits, glycemic traits, and markers of inflammation. Risk factors showing compelling evidence of a causal association with risk for at least one cancer type include alcohol consumption (for head/neck and colorectal), adult body mass index (increases risk for multiple cancers, but decreases risk for breast), height (increases risk for breast, colorectal, and lung; decreases risk for esophageal), telomere length (increases risk for lung adenocarcinoma, melanoma, renal cell carcinoma, glioma, B-cell lymphoma subtypes, chronic lymphocytic leukemia, and neuroblastoma), and hormonal factors (affects risk for sex steroid-sensitive cancers).
This review highlights alcohol consumption, body mass index, height, telomere length, and the hormonal exposures as factors likely to contribute to cancer causation. This review also highlights the need to study specific cancer types, ideally subtypes, as the effects of risk factors can be heterogeneous across cancer types. As consortia-based genome-wide association studies increase in sample size and analytical methods for MR continue to become more sophisticated, MR will become an increasingly powerful tool for understanding cancer causation.
KeywordsMendelian randomization Causal inference Cancer risk Instrumental variable
U01HG007601 (BLP), R01 ES020506 (BLP), and P01CA134294 (PK)
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflicts of interest.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
Papers of particular interest, published recently, have been highlighted as: • Of importance
- 4.Pierce B, Burgess S. Efficient design for Mendelian randomization studies: subsample and two-sample instrumental variable estimators. Am J Epidemiol. 2013;177:S117-S.Google Scholar
- 9.Bonilla C, Gilbert R, Kemp JP, Timpson NJ, Evans DM, Donovan JL, et al. Using genetic proxies for lifecourse sun exposure to assess the causal relationship of sun exposure with circulating vitamin D and prostate cancer risk. Cancer Epidemiol Biomark Prev. 2013;22:597–606. https://doi.org/10.1158/1055-9965.EPI-12-1248.CrossRefGoogle Scholar
- 10.Theodoratou E, Palmer T, Zgaga L, Farrington SM, McKeigue P, Din FVN, et al. Instrumental variable estimation of the causal effect of plasma 25-hydroxy-vitamin D on colorectal cancer risk: a Mendelian randomization analysis. PLoS One. 2012;7:e37662. https://doi.org/10.1371/journal.pone.0037662.CrossRefPubMedPubMedCentralGoogle Scholar
- 18.Taylor AE, Martin RM, Geybels MS, Stanford JL, Shui I, Eeles R, et al. Investigating the possible causal role of coffee consumption with prostate cancer risk and progression using Mendelian randomization analysis. Int J Cancer. 2017;140:322–8. https://doi.org/10.1002/ijc.30462.CrossRefPubMedGoogle Scholar
- 19.Timpson NJ, Brennan P, Gaborieau V, Moore L, Zaridze D, Matveev V, et al. Can lactase persistence genotype be used to reassess the relationship between renal cell carcinoma and milk drinking? Potentials and problems in the application of Mendelian randomization. Cancer Epidemiol Biomark Prev. 2010;19:1341–8. https://doi.org/10.1158/1055-9965.EPI-09-1019.CrossRefGoogle Scholar
- 20.Bergholdt HKM, Nordestgaard BG, Varbo A, Ellervik C. Lactase persistence, milk intake, and mortality in the Danish general population: a Mendelian randomization study. Eur J Epidemiol. 2017; https://doi.org/10.1007/s10654-017-0328-x.
- 26.Carreras-Torres R, Johansson M, Haycock PC, Wade KH, Relton CL, Martin RM, et al. Obesity, metabolic factors and risk of different histological types of lung cancer: a Mendelian randomization study. PLoS One. 2017;12:e0177875. https://doi.org/10.1371/journal.pone.0177875.CrossRefPubMedPubMedCentralGoogle Scholar
- 27.Painter JN, O'Mara TA, Marquart L, Webb PM, Attia J, Medland SE, et al. Genetic risk score Mendelian randomization shows that obesity measured as body mass index, but not waist:hip ratio, is causal for endometrial cancer. Cancer Epidemiol Biomark Prev. 2016;25:1503–10. https://doi.org/10.1158/1055-9965.EPI-16-0147.CrossRefGoogle Scholar
- 28.Nead KT, Sharp SJ, Thompson DJ, Painter JN, Savage DB, Semple RK, et al. Evidence of a causal association between insulinemia and endometrial cancer: a Mendelian randomization analysis. J Natl Cancer Inst. 2015;107 https://doi.org/10.1093/jnci/djv178.
- 31.Carreras-Torres R, Johansson M, Gaborieau V, Haycock PC, Wade KH, Relton CL, et al. The role of obesity, type 2 diabetes, and metabolic factors in pancreatic cancer: a Mendelian randomization study. J Natl Cancer Inst. 2017;109 https://doi.org/10.1093/jnci/djx012.
- 32.Thrift AP, Shaheen NJ, Gammon MD, Bernstein L, Reid BJ, Onstad L, et al. Obesity and risk of esophageal adenocarcinoma and Barrett’s esophagus: a Mendelian randomization study. J Natl Cancer Inst. 2014;106 https://doi.org/10.1093/jnci/dju252.
- 33.Guo Y, Warren Andersen S, Shu X-O, Michailidou K, Bolla MK, Wang Q, et al. Genetically predicted body mass index and breast cancer risk: Mendelian randomization analyses of data from 145,000 women of European descent. PLoS Med. 2016;13:e1002105. https://doi.org/10.1371/journal.pmed.1002105.CrossRefPubMedPubMedCentralGoogle Scholar
- 34.Davies NM, Gaunt TR, Lewis SJ, Holly J, Donovan JL, Hamdy FC, et al. The effects of height and BMI on prostate cancer incidence and mortality: a Mendelian randomization study in 20,848 cases and 20,214 controls from the PRACTICAL consortium. Cancer Causes Control. 2015;26:1603–16. https://doi.org/10.1007/s10552-015-0654-9.CrossRefPubMedPubMedCentralGoogle Scholar
- 38.Khankari NK, Shu X-O, Wen W, Kraft P, Lindstrom S, Peters U, et al. Association between adult height and risk of colorectal, lung, and prostate cancer: results from meta-analyses of prospective studies and Mendelian randomization analyses. PLoS Med. 2016;13:e1002118. https://doi.org/10.1371/journal.pmed.1002118.CrossRefPubMedPubMedCentralGoogle Scholar
- 39.Thrift AP, Risch HA, Onstad L, Shaheen NJ, Casson AG, Bernstein L, et al. Risk of esophageal adenocarcinoma decreases with height, based on consortium analysis and confirmed by Mendelian randomization. Clin Gastroenterol Hepatol. 2014;12:1667–76e1. https://doi.org/10.1016/j.cgh.201401.039.CrossRefPubMedPubMedCentralGoogle Scholar
- 41.Machiela MJ, Hsiung CA, Shu X-O, Seow WJ, Wang Z, Matsuo K, et al. Genetic variants associated with longer telomere length are associated with increased lung cancer risk among never-smoking women in Asia: a report from the female lung cancer consortium in Asia. Int J Cancer. 2015;137:311–9. https://doi.org/10.1002/ijc.29393.CrossRefPubMedGoogle Scholar
- 43.Iles MM, Bishop DT, Taylor JC, Hayward NK, Brossard M, Cust AE, et al. The effect on melanoma risk of genes previously associated with telomere length. J Natl Cancer Inst. 2014;106 https://doi.org/10.1093/jnci/dju267.
- 48.Walsh KM, Whitehead TP, de Smith AJ, Smirnov IV, Park M, Endicott AA, et al. Common genetic variants associated with telomere length confer risk for neuroblastoma and other childhood cancers. Carcinogenesis. 2016;37:576–82. https://doi.org/10.1093/carcin/bgw037.CrossRefPubMedPubMedCentralGoogle Scholar
- 50.• Haycock PC, Burgess S, Nounu A, Zheng J, Okoli GN, Bowden J et al. Association between telomere length and risk of cancer and non-neoplastic diseases: a Mendelian randomization study. JAMA Oncol. 2017. https://doi.org/10.1001/jamaoncol.2016.5945. This meta-analysis provides MR estimates for the effect of telomere length on risk for various cancers and other chronic diseases.
- 56.He L, Culminskaya I, Loika Y, Arbeev KG, Bagley O, Duan M, et al. Causal effects of cardiovascular risk factors on onset of major age-related diseases: a time-to-event Mendelian randomization study. Exp Gerontol. 2017; https://doi.org/10.1016/j.exger.2017.09.019.
- 60.Nimptsch K, Song M, Aleksandrova K, Katsoulis M, Freisling H, Jenab M, et al. Genetic variation in the ADIPOQ gene, adiponectin concentrations and risk of colorectal cancer: a Mendelian randomization analysis using data from three large cohort studies. Eur J Epidemiol. 2017;32:419–30. https://doi.org/10.1007/s10654-017-0262-y.CrossRefPubMedPubMedCentralGoogle Scholar
- 62.Qu K, Pang Q, Lin T, Zhang L, Gu M, Niu W, et al. Circulating interleukin-10 levels and human papilloma virus and Epstein-Barr virus-associated cancers: evidence from a Mendelian randomization meta-analysis based on 11,170 subjects. OncoTargets Ther. 2016;9:1251–67. https://doi.org/10.2147/OTT.S96772.CrossRefGoogle Scholar
- 63.Niu W, Pang Q, Lin T, Wang Z, Zhang J, Tai M, et al. A causal role of genetically elevated circulating interleukin-10 in the development of digestive cancers: evidence from Mendelian randomization analysis based on 29,307 subjects. Medicine. 2016;95:e2799. https://doi.org/10.1097/MD.0000000000002799.CrossRefPubMedPubMedCentralGoogle Scholar
- 67.Legason ID, Pfeiffer RM, Udquim K-I, Bergen AW, Gouveia MH, Kirimunda S, et al. Evaluating the causal link between malaria infection and endemic Burkitt lymphoma in Northern Uganda: a Mendelian randomization study. EBioMedicine. 2017;25:58–65. https://doi.org/10.1016/j.ebiom.2017.09.037.CrossRefPubMedPubMedCentralGoogle Scholar
- 69.• Day FR, Thompson DJ, Helgason H, Chasman DI, Finucane H, Sulem P, et al. Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk. Nat gGenet. 2017;49:834–41. https://doi.org/10.1038/ng.3841. This study provides evidence of causal links between timing of puberty and risk for breast, endometrial, and prostate cancers.CrossRefGoogle Scholar
- 75.Bonilla C, Lewis SJ, Rowlands M-A, Gaunt TR, Davey Smith G, Gunnell D, et al. Assessing the role of insulin-like growth factors and binding proteins in prostate cancer using Mendelian randomization: genetic variants as instruments for circulating levels. Int J Cancer. 2016;139:1520–33. https://doi.org/10.1002/ijc.30206.CrossRefPubMedPubMedCentralGoogle Scholar
- 76.Lu W-Q, Qiu J-L, Huang Z-L, Liu H-Y. Enhanced circulating transforming growth factor beta 1 is causally associated with an increased risk of hepatocellular carcinoma: a Mendelian randomization meta-analysis. Oncotarget. 2016;7:84695–704. https://doi.org/10.18632/oncotarget.13218.PubMedPubMedCentralCrossRefGoogle Scholar
- 78.Huang Q, Mi J, Wang X, Liu F, Wang D, Yan D, et al. Genetically lowered concentrations of circulating sRAGE might cause an increased risk of cancer: meta-analysis using Mendelian randomization. J Int Med Res. 2016;44:179–91. https://doi.org/10.1177/0300060515617869. CrossRefPubMedPubMedCentralGoogle Scholar
- 89.• Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44:512–25. https://doi.org/10.1093/ije/dyv080. The method described in this paper, MR-Egger, is one of the several methods available for generating MR estimates that can be robust to violations of the MR assumptions caused by pleiotropic SNPs.CrossRefPubMedPubMedCentralGoogle Scholar